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<table width="100%" summary="page for respdis"><tr><td>respdis</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Clustered Ordinal Respiratory Disorder</h2>

<h3>Description</h3>

<p>The <code>respdis</code> data frame has 111 rows and 3 columns. The study described
in Miller et. al. (1993) is a randomized clinical trial of a new treatment of
respiratory disorder. The study was conducted in 111 patients who were
randomly assigned to one of two treatments (active, placebo). At each of four
visits during the follow-up period, the response status of each patients was
classified on an ordinal scale.
</p>


<h3>Usage</h3>

<pre>
respdis
</pre>


<h3>Format</h3>

<p>This data frame contains the following columns:
</p>

<dl>
<dt>y1, y2, y3, y4</dt><dd><p>ordered factor measured at 4 visits for the response with
levels, <code>1</code> &lt; <code>2</code> &lt; <code>3</code>, 1 = poor, 2 = good, and 3 =
excellent</p>
</dd>
<dt>trt</dt><dd><p>a factor for treatment with levels, 1 = active, 0 =
placebo.</p>
</dd>
</dl>


<h3>References</h3>

<p>Miller, M.E., David, C.S., and Landis, R.J. (1993) The analysis
of longitudinal polytomous data: Generalized estimating equation and
connections with weighted least squares, <em>Biometrics</em> <b>49</b>:
1033-1048.
</p>


<h3>Examples</h3>

<pre>

data(respdis)
resp.l &lt;- reshape(respdis, varying = list(c("y1", "y2", "y3", "y4")),
                  v.names = "resp", direction = "long")
resp.l &lt;- resp.l[order(resp.l$id, resp.l$time),]
fit &lt;- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE)
summary(fit)

z &lt;- model.matrix( ~ trt - 1, data = respdis)
ind &lt;- rep(1:111, 4*3/2 * 2^2)
zmat &lt;- z[ind,,drop=FALSE]
fit &lt;- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE,
              z = zmat, corstr = "exchangeable")
summary(fit)

</pre>


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